Additional file 1 of Long-term treatment patterns and survival in metastatic breast cancer by intrinsic subtypes – an observational cohort study in Sweden

Additional file 1: Table 1. Intrinsic subtype defined at primary diagnosis or re-biopsy

Additional file 2 of Long-term treatment patterns and survival in metastatic breast cancer by intrinsic subtypes – an observational cohort study in Sweden

Additional file 2: Table 2. Proportion of time on active treatment among patients by metastatic subtype

Period, age, histology, socioeconomic status and gender distributions in relative pairs with lung cancer.

<p>Period, age, histology, socioeconomic status and gender distributions in relative pairs with lung cancer.</p

Risk of lung cancer-specific death in proband's relative (child, sibling, spouse) depending on proband survival.

a<p>Multivariate proportional hazard (Cox) model adjusted for calendar year of diagnosis and age at diagnosis.</p>b<p>One degree of freedom.</p>c<p>Multivariate proportional hazard (Cox) model adjusted for calendar year, age and place of diagnosis, socioeconomic status, tumour histology and gender.</p>d<p>Parents (Spouses) diagnosed between January 1961 and December 2001.</p>e<p>Children (siblings) diagnosed between January 1991 and December 2001.</p

Effect of satiety factor infusions on serum levels of human MIC-1/GDF15.

<p>(A) Subjects receiving CCK-8 infusion alone had significant time dependent increase in serum levels of MIC-1/GDF15 with significant increases at 120, 150 and 180 minutes of infusion. Infusion of GLP-1 or CCK plus GLP-1 had no significant effect on serum MIC-1/GDF15 level (<i>n</i> = 9, <i>vehicle vs GLP-1</i>, <i>p</i> = 0.2; <i>vehicle vs CCK-8 + GLP-1</i>, <i>p</i> = 0.06). (B) PYY1-36 or PYY3-36 or saline was infused in subjects that were fasted overnight and had a 310-Kcal meal. Neither PYY1-36 nor PYY3-36 infusions had a significant effect on serum MIC-1/GDF15 levels (<i>n</i> = 8, <i>vehicle vs PYY1-36</i>, <i>p</i> = 0.18; <i>vehicle vs PYY3-36</i>, <i>p</i> = 0.34). Data were analysed by ANOVA <i>with Bonferroni correction</i> and are presented as mean ± s.e.m. * represents <i>p</i> < 0.05.</p

Correlation of monozygotic within-pair differences in MIC-1/GDF15 serum levels and within-pair differences in BMI.

<p>Correlation between within twin-pair difference in serum MIC-1/GDF15 levels and within twin-pair difference in BMI (<i>n</i> = 72 twins), performed by Spearman regression, identifies a highly significant correlation. In general the twin of the twin pair with a higher serum MIC-1/GDF15 level generally had a lower BMI than their identical twin pair. The reverse was also true.</p

Fasting diurnal variation of human MIC-1/GDF15 serum levels.

<p>Serum MIC-1/GDF15 levels were measured on blood sample taken from participants every 30min during a 24h period. The oscillatory pattern of serum MIC-1/GDF15 levels for each individual subject was fitted to a cosine curve function.</p

Postprandial changes in human MIC-1/GDF15 serum levels.

<p>Changes in serum MIC-1/GDF15 levels over time were measured in 17 subjects that received 5 different isocaloric meals on 5 separate occasions. (A) Changes in MIC-1/GDF15 serum levels do not differ for the 5 subjects fed the 5 different meals (<i>n</i> = 17, <i>p</i> = 0.26 <i>repeated measure ANOVA</i>). (B) When average data from all meals was pooled and normalised to baseline concentrations, there was significant time dependent alteration in circulating MIC-1/GDF15 levels (<i>n</i> = 5 meal; 17 subject/meal, <i>p</i> < 0.001 <i>one-way ANOVA</i>). (C) The postprandial profile of MIC-1/GDF15 serum levels (red) described in panel B were not significantly from its 24 h oscillatory pattern (<i>p</i> = 0.28, <i>repeated measure ANOVA</i>). Data represented as mean ± s.e.m.</p

Time of day for maximum and minimum MIC-1/GDF15 serum levels.

<p>Time of day for maximum and minimum MIC-1/GDF15 serum levels.</p

PrCa association information for SNPs significant at <i>P</i><10⁻⁶ in the iCOGS imputed data.

<p><b>Uni</b> denotes data from univariate analyses and <b>Multi</b> the results after conditional regression analysis. rs138213197 could not be accurately imputed into the iCOGS sample set and was analysed in directly genotyped samples only.</p>#<p>Minor Allele Frequency in our control sample set.</p>$<p>Analyses were performed on the full iCOGS data set of 20,440 cases and 21,469 controls.</p>*<p>Analyses were performed on the subset of 5500 cases and 4923 controls genotyped for both rs138213197 and rs117576373.</p